NFAT Tree Structure for Network Condition Correlation
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Solution Overview
Problem
Conventional network systems are inflexible and inefficient in determining the status of complex network conditions, failing to effectively collect, analyze, and report information necessary for scalable and dependable network performance, accessibility, and deployment.
Innovation Solution
A correlation policy application and management system utilizing a non-deterministic finite automata tree (NFAT) structure for evaluating complex network conditions, enabling simultaneous correlation of multiple events and policies, and facilitating massively parallel streaming analytics and data access, while minimizing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional network systems are used to determine network status, then the system structure is simple, but the system is inflexible and inefficient in determining complex network conditions
Solution Approach 1:
The patent segments complex network condition determination into multiple hierarchical levels: individual network element status, network condition patterns, and overall network status. This segmentation allows the system to handle complex conditions by breaking them down into manageable components that can be processed independently and then combined, thereby improving flexibility without overwhelming system complexity.
Solution Approach 2:
The patent introduces a temporal dimension to network monitoring by analyzing network conditions across multiple time points and identifying patterns over time. This dimensional approach enables the system to detect complex conditions that require temporal context, such as gradual degradation or cyclic patterns, enhancing adaptability while maintaining structured processing.
2Productivity
If conventional methods are used to collect and analyze network information, then resource consumption is low, but the system is inefficient in analyzing complex network conditions
Solution Approach 1:
The patent implements preliminary action by pre-defining network condition patterns and rules before actual network monitoring begins. These pre-configured patterns include common network issues, their symptoms, and required actions. When monitoring network elements, the system simply matches observed conditions against these pre-defined patterns, dramatically improving analysis efficiency without requiring complex real-time computation, thus maintaining low resource consumption.
Solution Approach 2:
The patent uses copying by creating standardized templates for network condition patterns that can be replicated and applied across multiple network elements. Instead of analyzing each network condition from scratch, the system copies and applies pre-defined pattern templates, reducing computational overhead and improving efficiency while consuming fewer resources.
3Adaptability or versatility
If the system monitors complex network conditions with multiple conditions, then the network performance is scalable and flexible, but the device complexity increases
Solution Approach 1:
The patent implements dynamics by making the network monitoring system adaptable and configurable. The system allows dynamic addition and modification of network condition patterns, rules, and thresholds without requiring changes to the underlying system architecture. This dynamic capability enables scalable network performance monitoring while keeping the correlation engine's core structure simple and manageable.
Data Source
AI summary
A method includes processing event data to detect a status of a network function. The event data is processed based on two or more conditions defined by a correlation policy. The correlation policy includes a non-deterministic finite automata tree (NFAT) structure correlation policy having a policy type and a logic-gate. The method additionally includes determining the policy type of the NFAT structure correlation policy. The method also includes determining whether a first value of the two or more conditions is indicative of whether a first condition is satisfied. The method further includes determining whether a second value of the two or more conditions is indicative of whether the second condition is satisfied. The method additionally includes determining whether the NFAT structure correlation policy is satisfied based on the first value, the second value, the logic-gate and the policy type.